Atmospheric Concentration of Carbon Dioxide (CO2)#
Highlights
Over the last 68 years, the concentration of carbon dioxide (CO2) in the atmosphere measured at NOAA’s Mauna Loa Observatory has increased by more than 112 parts per million (ppm), to an annual average value over 424 ppm in 2024.
The annual average rate of increase in CO2 since 1958 at Mauna Loa is more than 1.65 ppm per year.
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import os
import os.path as op
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import scipy.stats as sp
from myst_nb import glue
from IPython.display import HTML
import sys
sys.path.append("../../../functions")
from data_downloaders import download_HOT_CO2_data, download_MLO_CO2_data
sys.path.append("../../../../indicators_setup")
from ind_setup.plotting import plot_timeseries
from ind_setup.plotting_int import plot_timeseries_interactive, fig_int_to_glue
from ind_setup.tables import plot_df_table
Observations from NOAA#
Databases used:
Atmospheric C02 from the Muana Loa Observatory (ESRL at NOAA)
update_data = True
path_data = "../../../data"
url = 'https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_mm_mlo.txt'
if update_data:
MLO_data = download_MLO_CO2_data(url)
MLO_data.to_pickle(op.join(path_data, 'MLO_co2.pkl'))
else:
MLO_data = pd.read_pickle(op.join(path_data, 'MLO_co2.pkl'))
Plotting#
Muana Loa Observatory
dict_plot = [{'data' : MLO_data, 'var' : 'CO2', 'ax' : 1, 'label' : 'MLO: CO2'},]
MLO_data['CO2_deseasoned'] = MLO_data['CO2'].rolling(window=12, center=True).mean()
glue("n_years", len(np.unique(MLO_data.index.year)), display=False)
glue("co2_2024", int(MLO_data.loc['2024'].CO2.mean()), display=False)
glue("start_year", MLO_data.dropna().index[0].year, display=False)
dict_plot = [{'data' : MLO_data, 'var' : 'CO2', 'ax' : 1, 'trendline' : True, 'label' : 'MLO: CO2'},
{'data' : MLO_data, 'var' : 'CO2_deseasoned', 'ax' : 1, 'trendline' : False, 'label' : 'MLO: CO2 (Deseasoned)'}]
fig, trend = plot_timeseries_interactive(dict_plot, trendline=True, figsize=(20, 10), return_trend=True);
glue("trend", float(trend[0]), display=False)
glue("change", float(trend[0]*len(np.unique(MLO_data.index.year))), display=False)
glue("trend_fig", fig_int_to_glue(fig), display=False)
Fig. Monthly Mean Concentration of Atmospheric CO2 at Mauna Loa since 1958. The blue line represents the monthly mean values, centered on the middle of each month. The red line represents the same, after correction for the average seasonal cycle. The solid black line represents the trend, which is statistically significant (p < 0.05). The annual oscillations at Mauna Loa are due to the seasonal imbalance between the photosynthesis and respiration of plants on land. From NOAA ESRL Global Monitoring Division. https://www.esrl.noaa.gov/gmd/ccgg/trends/
Show code cell source
from scipy.stats import linregress
MLOy = MLO_data[['CO2']].groupby(MLO_data.index.year).mean()
MLOy.index = pd.to_datetime(MLOy.index, format = '%Y')
Annual Stats
d = MLOy.describe()
d.loc['Rate of change'] = trend
fig = plot_df_table(np.round(d, 2), figsize = (400, 400))
